# vim: set fileencoding=utf-8 :
# Pavel Korshunov <email@example.com>
# Tue 11 Oct 15:43:22 2016
This is the implementation of VoicePA database high level interface for verification experiments.
It is an extension of an SQL-based database interface, which directly talks to VoicePA database, for
verification experiments (good to use in bob.bio.base framework).
from bob.bio.base.database import BioDatabase
from bob.bio.spear.database import AudioBioFile
def __init__(self, f):
Initializes this File object with an File equivalent from the underlying SQl-based interface for
super(VoicePABioFile, self).__init__(client_id=f.client_id, path=f.path, file_id=f.id)
self.__f = f
Implements verification API for querying VoicePA database.
def __init__(self, **kwargs):
# call base class constructors to open a session to the database
super(VoicePABioDatabase, self).__init__(name='voicepa', **kwargs)
from bob.db.voicepa.query import Database as LowLevelDatabase
self._db = LowLevelDatabase()
self.low_level_group_names = ('train', 'dev', 'eval')
self.high_level_group_names = ('world', 'dev', 'eval')
[docs] def model_ids_with_protocol(self, groups=None, protocol=None, gender=None):
groups = self.convert_names_to_lowlevel(groups, self.low_level_group_names, self.high_level_group_names)
return [client.id for client in self._db.clients(groups=groups, gender=gender)]
[docs] def objects(self, protocol=None, purposes=None, model_ids=None, groups=None, **kwargs):
# convert group names from the conventional in verification experiments to the internal database names
if groups is None: # all groups are assumed
groups = self.high_level_group_names
matched_groups = self.convert_names_to_lowlevel(groups, self.low_level_group_names, self.high_level_group_names)
# this conversion of the protocol with appended '-licit' or '-spoof' is a hack for verification experiments.
# To adapt spoofing databases to the verification experiments, we need to be able to split a given protocol
# into two parts: when data for licit (only real/genuine data is used) and data for spoof (attacks are used instead
# of real data) is used in the experiment. Hence, we use this trick with appending '-licit' or '-spoof' to the
# protocol name, so we can distinguish these two scenarios.
# By default, if nothing is appended, we assume licit protocol.
# The distinction between licit and spoof is expressed via purposes parameters
# this is the difference in terminology.
# lets check if we have an appendix to the protocol name
appendix = None
appendix = protocol.split('-')[-1]
# if protocol was empty or there was no correct appendix, we just assume the 'licit' option
if not (appendix == 'licit' or appendix == 'spoof'):
appendix = 'licit'
# put back everything except the appendix into the protocol
protocol = '-'.join(protocol.split('-')[:-1])
# if protocol was empty, we set it to the grandtest, which is the whole data
if not protocol:
protocol = 'grandtest'
correct_purposes = purposes
# licit protocol is for real access data only
if appendix == 'licit':
# by default we assume all real data
if purposes is None:
correct_purposes = ('enroll', 'probe')
# spoof protocol uses real data for enrollment and spoofed data for probe
# so, probe set is the same as attack set
if appendix == 'spoof':
# by default we return attacks only for 'world' group
# and (enroll:realdata + probe:attackdata) for dev and eval
if purposes is None:
correct_purposes = ('attack',) if 'train' in matched_groups else ('enroll', 'attack')
# otherwise replace 'probe' with 'attack'
elif isinstance(purposes, (tuple, list)):
correct_purposes = 
for purpose in purposes:
if purpose == 'probe':
correct_purposes += ['attack']
correct_purposes += [purpose]
elif purposes == 'probe':
correct_purposes = ('attack',)
# now, query the actual VoicePA database
objects = self._db.objects(protocol=protocol, groups=matched_groups, cls=correct_purposes,
# make sure to return BioFile representation of a file, not the database one
return [VoicePABioFile(f) for f in objects]
[docs] def annotations(self, file):